The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Frequency and Phase Mixed Coding in SSVEP-Based Brain--Computer Interface
Abstract
Frequency coding has been the traditional method implemented in steady-state visual evoked potential (SSVEP)-based brain--computer interfaces (BCI). However, it is limited in terms of possible target numbers and, consequently, inappropriate for certain applications involving liquid crystal display (LCD) with multiple stimuli. This paper proposes an innovative coding method for SSVEP that, through a combination of frequency and phase, increases the number of targets, thus it improves the information transfer rate (ITR). With this method, a BCI system with 15 targets was developed using three stimulus frequencies, which is five times as many targets as the traditional method. Additionally, this paper defines the concept of reference phase, and decodes the EEG by means of Fourier coefficient projections onto the reference phase directions. Through the optimization of lead position, reference phase, data segment length, and harmonic components, the average ITR exceeded 60 bits/min in a simulated online test with ten subjects.
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Cites
Delorme, A., & Makeig, S. (2004) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2003.10.009 · Cited by 24,371
Brain–computer interfaces for communication and control
Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T. M. (2002) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00057-3 · Cited by 7,927
Brain-Computer Interfaces Based on Visual Evoked Potentials
Wang, Y., Gao, X., Hong, B., Jia, C., & Gao, S. (2008) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2008.923958 · Cited by 423
Self-citation
Cited by
Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review
Congedo, M., Barachant, A., & Bhatia, R. (2017) · Brain-Computer Interfaces · doi:10.1080/2326263x.2017.1297192 · Cited by 456
Visual and Auditory Brain–Computer Interfaces
Gao, S., Wang, Y., Gao, X., & Hong, B. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2300164 · Cited by 449
Self-citationNakanishi, M., Wang, Y., Wang, Y.-T., & Jung, T.-P. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140703 · Cited by 376
A Dynamically Optimized SSVEP Brain–Computer Interface (BCI) Speller
Yin, E., Zhou, Z., Jiang, J., Yu, Y., & Hu, D. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2320948 · Cited by 254
A New Generation of Brain-Computer Interface Based on Riemannian Geometry
Congedo, M., Barachant, A., & Andreev, A. (2013) · arXiv · doi:10.48550/arxiv.1310.8115 · Cited by 69
Metadata
- Authors
- Jia, C., Gao, X., Hong, B., & Gao, S.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2011-01
- Volume
- 58
- Issue
- 1
- Pages
- 200-206
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W1974609966
- Cited by
- 197
- References
- 3
- FWCI
- 7.42
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jia, C., Gao, X., Hong, B., & Gao, S. (2011). Frequency and Phase Mixed Coding in SSVEP-Based Brain--Computer Interface. IEEE Transactions on Biomedical Engineering. https://doi.org/10.1109/tbme.2010.2068571
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